lpynn
This is a basic neural network package consisting of a single perceptron node. It can do binary classification.
Usage
Example:
from lpynn.perceptron import init_perceptron, print_perceptron, normalize_input_vectors, Perceptron, train_dataset
from lpython import i32, f64
def main0():
p: Perceptron = Perceptron(0, [0.0], 0.0, 0, 0.0, 0.0, 0)
init_perceptron(p, 2, 0.05, 10000, 90.0)
print_perceptron(p)
print("=================================")
input_vectors: list[list[f64]] = [[-1.0, -1.0], [-1.0, 1.0], [1.0, -1.0], [1.0, 1.0]]
outputs: list[i32] = [1, 1, 1, -1]
normalize_input_vectors(input_vectors)
train_dataset(p, input_vectors, outputs)
print_perceptron(p)
main0()
1 maintainer
Metadata
1 maintainer
Release files for lpynn 0.0.1.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| lpynn-0.0.1.4.tar.gz | 4.8 kB | Without provenance | Details for lpynn-0.0.1.4.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| lpynn-0.0.1.4-py3-none-any.whl | Python 3 | none | any | Details for lpynn-0.0.1.4-py3-none-any.whl |
Total release size: 10.7 kB
Release files / lpynn-0.0.1.4.tar.gz
| Download URL | lpynn-0.0.1.4.tar.gz |
|---|---|
| Size | 4.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.11.3
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Release files / lpynn-0.0.1.4-py3-none-any.whl
| Download URL | lpynn-0.0.1.4-py3-none-any.whl |
|---|---|
| Size | 5.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
3f7be19aee4abef8263b15d5320b05546047ef4d2d4140cfcf753bf654be2390
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.11.3
|
Security for lpynn 0.0.1.4
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